Hi there 👋

Hi — I'm a builder of production ML systems & LLM tooling 👋

I design and ship full-stack AI/ML products: fine-tuning and deploying LLMs, agent workflows, scalable data pipelines, and production inference stacks (Docker / Kubernetes / on-prem GPU). I like projects that connect research-y models to real-world systems and measurable outcomes.

🔭 Current focus

Post-training / PEFT (QLoRA, LoRA) for LLMs and agentic systems

Fast, reproducible model deployment (vLLM, Ollama, LangGraph, containerized stacks)

Production data pipelines and feature engineering for high-throughput environments

🛠 Tech highlights

Python · PyTorch · TensorFlow · PEFT/QLoRA · vLLM · LangGraph · Docker · Kubernetes / OpenShift · Go · Angular · Spark · Polars · Snowflake · REST / gRPC · CV (real-time inference)

⭐ Selected projects

Click each project to open the repo.

MiniMind — Chinese → English Translation Agent

A LangGraph + vLLM translation agent that performs multi-pass translation, quality validation and automatic fixes — built to create a high-quality zh→en dataset and production translation pipeline.

PEFT Fine-Tuning Recipes — Classification

Hands-on PEFT recipes and scripts (QLoRA / LoRA) for classification tasks: reproducible examples, training configs and evaluation scripts.

Stable Diffusion WebUI — Docker

One-click Docker setup for Stable Diffusion WebUI, with GPU support and common model installers — intended for local image generation and experimentation.

SMB File Server

Lightweight SMB file server templates and deployment scripts for self-hosted file sharing.

Attendance System

A simple attendance / check-in system (web + API) built for easy deployment and integration with internal tools.

TabularML

Experiments and templates for tabular machine learning workflows: feature engineering, model baselines, and model evaluation scripts.

People-Counting in Real-Time

Real-time computer-vision pipeline for estimating crowd/people counts from video streams with lightweight inference optimizations.

📂 How I organize repos

Reproducible examples (Docker + scripts) so others can run locally or on a GPU node

Clear README with quickstart + minimal config for common dev environments (macOS / Linux)

Small, focused notebooks and tests for core functionality